Individual Variation Research Articles

Unlocking Organizational Commitment through Individual Traits and Job Satisfaction: A Millennial and Gen Z Perspective in West Borneo

Background and Purpose: This study aims to investigate the combined effects of individual characteristics, job redesign, and transformational leadership on various outcome variables, including job satisfaction, job stress and organizational commitment. Methodology: This research is a descriptive quantitative research with a sample size of 110 millennial and generation Z workers. Data testing was carried out using the PLS-SEM method. Findings: The research results show that individual character variables have a significant effect on job satisfaction, job stress, and organizational commitment. Transformational leadership style is proven to have a significant effect on job satisfaction, job redesign, and organizational commitment, but does not have a significant effect on individual character. Job redesign was found to have a significant effect on job satisfaction, individual character, and job stress. Job satisfaction has a significant effect on organizational commitment, but does not have a significant effect on job stress. For the mediation effect, individual character is able to mediate the relationship between job redesign and job satisfaction and job stress, while job satisfaction is only able to mediate the relationship between transformational leadership style and organizational commitment. Contributions: Similar research conducted in developing countries and open in city centers is still very rare, even though the existing phenomena are interesting to study because there will be many differences that can be found both from individuals and even the environment, therefore this research facilitates this so that results can be obtained. this research.

Homogenization of soil seed bank communities by fire and invasive species in the Mojave Desert

Soil seed banks help maintain species diversity through temporal storage effects and function as germination pools that can optimize fitness across varying environmental conditions. These characteristics promote the persistence of native plant communities, yet disturbances such as fire and associated invasions by non-native species can disrupt these reserves, fundamentally altering successional trajectories. This may be particularly true in deserts, where native plant communities are less adapted to fire. While studies of fire effects on desert plant communities are not uncommon, information regarding the short- and long-term effects of fire on seed banks is less available. To better understand the influence of fire and invasive species on desert seed banks, we investigated soil seed bank biodiversity from 30 wildfires that burned between 1972 and 2010 across the Mojave Desert ecoregion of North America. We assessed how characteristics of fire regimes (frequency, time since fire, and burn severity) interacted with climate and invasive plants on measures of α-, β-, and γ-diversities. Because β-diversity is a direct measure of community variability and reveals important information about biodiversity loss, we further examined the nestedness and turnover components of β-diversity. Mean α- and γ-diversities were generally higher for burned locations than in unburned reference sites, however individual fire variables had little influence on patterns of seed bank diversity. Burned area seed banks tended to be dominated by non-native invasive species, primarily two grasses, (Bromus rubens, Bromus tectorum), as well as an invasive forb (Erodium cicutarium). The most striking pattern we observed was a collective sharp decline in α-, β-, and γ-diversities with increased invasive species dominance, indicating the homogenization of seed bank communities with the colonization of invasive species after fire. Evidence of homogenization was further supported by reduced turnover and increased nestedness in burn areas compared to reference areas indicating potential biodiversity loss. Our findings highlight how biological processes such as plant invasions can combine with disturbance from fire to alter patterns of seed bank composition and diversity in desert ecosystems.

Estimating kill intervals for a specific prey species using location clusters from GPS-collared Eurasian lynx (Lynx lynx)

An increasing number of GPS telemetry studies have helped to gain important insights into predator-prey relationships in recent years. However, considerable time and effort is needed to evaluate whether GPS location clusters (GLCs) reflect predation events. To reduce field effort, predictive models are being developed to calculate predator kill intervals, but few studies have attempted to do this for a specific species of prey. Between 2013 and 2018, we studied predation by 13 GPS-collared Eurasian lynx (Lynx lynx) on Alpine chamois (Rupicapra rupicapra) in the northwestern Swiss Alps. Our objectives were to predict the total number of killed chamois, including potential kills in unchecked GLCs, and to evaluate if model predictions were sufficiently accurate. We built a set of generalized linear models (GLM) predicting the occurrence of GLCs containing lynx-killed chamois (1) versus GLCs containing other prey types or no prey (0) and compared their predictive performance by means of k-fold cross-validation. We found that model performance was very similar for all candidate models, with the full model yielding the best cross-validation result (accuracy = 0.83, sensitivity = 0.43, specificity = 0.94). Female lynx killed on average one chamois every 11.9 days (10.6–13.0 days, 95% CI); male lynx killed one chamois every 7.2 days (6.7–7.6 days, 95% CI). Our model showed high specificity for detecting non-chamois GLCs, but sensitivity for detection of GLCs with actual chamois kills was low. We conclude that the sensitivity of the models should be further improved, but the results can be sufficient for practical application. Predictive modelling approaches do not replace extensive fieldwork but require large sets of field data, high individual variability and thorough knowledge of a predator’s ecology and prey community. Our approach may provide useful results for binary classifications in rather simple predator-prey systems, but extrapolations from one study system to another might be difficult.

Patient-specific temperature distribution prediction in laser interstitial thermal therapy: single-irradiation data-driven method

Laser interstitial thermal therapy (LITT) is popular for treating brain tumours and epilepsy. The strict control of tissue thermal damage extent is crucial for LITT. Temperature prediction is useful for predicting thermal damage extent. Accurately predicting in vivo brain tissue temperature is challenging due to the temperature dependence and the individual variations in tissue properties. Considering these factors is essential for improving the temperature prediction accuracy. Objective. To present a method for predicting patient-specific tissue temperature distribution within a target lesion area in the brain during LITT. Approach. A magnetic resonance temperature imaging (MRTI) data-driven estimation model was constructed and combined with a modified Pennes bioheat transfer equation (PBHE) to predict patient-specific temperature distribution. In the PBHE for temperature prediction, the individual specificity and temperature dependence of thermal tissue properties and blood perfusion, as well as the individual specificity of optical tissue properties were considered. Only MRTI data during one laser irradiation were required in the method. This enables the prediction of patient-specific temperature distribution and the resulting thermal damage region for subsequent ablations. Main results. Patient-specific temperature prediction was evaluated based on clinical data acquired during LITT in the brain, using intraoperative MRTI data as the reference standard. Our method significantly improved the prediction performance of temperature distribution and thermal damage region. The average root mean square error was decreased by 69.54%, the average intraclass correlation coefficient was increased by 37.5%, the average Dice similarity coefficient was increased by 43.14% for thermal damage region prediction. Significance. The proposed method can predict temperature distribution and thermal damage region at an individual patient level during LITT, providing a promising approach to assist in patient-specific treatment planning for LITT in the brain.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension.

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Quantifying changes in oxygen saturation of the internal jugular vein in vivo using deep neural networks and subject-specific three-dimensional Monte Carlo models.

Central venous oxygen saturation (ScvO2) is an important parameter for assessing global oxygen usage and guiding clinical interventions. However, measuring ScvO2 requires invasive catheterization. As an alternative, we aim to noninvasively and continuously measure changes in oxygen saturation of the internal jugular vein (SijvO2) by a multi-channel near-infrared spectroscopy system. The relation between the measured reflectance and changes in SijvO2 is modeled by Monte Carlo simulations and used to build a prediction model using deep neural networks (DNNs). The prediction model is tested with simulated data to show robustness to individual variations in tissue optical properties. The proposed technique is promising to provide a noninvasive tool for monitoring the stability of brain oxygenation in broad patient populations.

A Multicenter Randomized Controlled Trial Of Microbiome-Based Artifıcial Intelligence-Assisted Personalized Diet Vs Low Fodmap Diet: A Novel Approach for the Management of Irritable Bowel Syndrome.

Personalized management strategies are pivotal in addressing Irritable Bowel Syndrome (IBS). This multicenter randomized controlled trial focuses on comparing the efficacy of a microbiome-based artificial intelligence (AI)-assisted personalized diet (PD) with a low FODMAP diet (LFD) for IBS management. One hundred and twenty-one patients participated, with 70 assigned to the PD group and 51 to the LFD group. IBS subtypes, demographics, symptom severity (IBS-SSS), anxiety, depression, and quality of life (IBS-QOL) were evaluated. Both interventions spanned 6 weeks. The trial's primary outcome was the within-individual difference in IBS-SSS compared between intervention groups. For the primary outcome, there was a change in IBS-SSS of -112.7 for those in the PD group vs -99.9 for those in the LFD group (p: 0.29). Significant improvement occurred in IBS-SSS scores (p<.001), frequency (p<.001), abdominal distension (p<.001), and life interference (p<.001) in both groups. Additionally, there were significant improvements in anxiety levels and IBS-QOL scores for both groups (p<.001). Importantly, PD was effective in reducing IBS SSS scores across all IBS subtypes IBS-C (p<.001), IBS-D (p=.01), and IBS-M (p<.001) subtypes, while LFD exhibited comparable improvements in IBS-C (p=.004) and IBS-M (p<.001). PD intervention significantly improved IBS-QOL scores for all subtypes (IBS-C (p<.001), IBS-D (p<.001), and IBS-M (p=.008)), while the LFD did so for the IBS-C (p=.004) and IBS-D (p=.022). Notably, PD intervention led to significant microbiome diversity shifts (p<0.05) and taxa alterations compared to LFD. The AI-assisted personalized diet emerges as a promising approach for comprehensive IBS management. With its ability to address individual variation, the PD approach demonstrates significant symptom relief, enhanced quality of life, and notable diversity shifts in the gut microbiome, making it a valuable strategy in the evolving landscape of IBS care.

About birds and bees, snails and trees: Children's ideas on animal and plant evolution

AbstractEvolution is the integrative framework of the life sciences. Even though the topic is often not formally introduced before high school, young children already have various ideas about evolutionary principles (variation, inheritance, and selection) and their underlying key concepts (e.g., differential fitness, reproduction, and speciation). Describing and refining those ideas has increasingly received attention over the last two decades. However, we see two scopes of improvement in the field: (1) There is a need to examine children's ideas about evolutionary concepts holistically rather than focusing at specific aspects. (2) Although research has shown that older students have different ideas about animal and plant evolution, there is little data on children's ideas about plant evolution to compare with their ideas about animal evolution. All of this results in an incomplete record of children's pre‐existing ideas that would help to design assessments or interventions. Consequently, we developed a set of questions, about the evolutionary principles and interviewed 24 kindergarten children. Most children had basic ideas about individual variation in animals and plants but experienced a lack of knowledge about the origin of variation. Most children seemed to acknowledge plants as living beings and reasoned equally about animals and plants for most concepts. However, many children failed to reason about reproduction and inheritance in plants because they believed plants would not reproduce sexually. Confronted with a selection scenario, most children struggled applying concepts previously shown on an individual level to a population level. Considering our findings, we propose ideas about how to measure and foster children's pre‐existing ideas about evolution.

Beyond Stages: Predicting Individual Time Dependent Risk for Type 1 Diabetes.

Essentially all individuals with multiple autoantibodies will develop clinical type 1 diabetes. Multiple AABs and normal glucose tolerance define Stage 1 diabetes; abnormal glucose tolerance defines Stage 2. However, the rate of progression within these stages is heterogeneous, necessitating personalized risk calculators to improve clinical implementation. We developed 3 models using TrialNet's Pathway to Prevention data to accommodate the reality that not all risk variables are clinically available. The Small model included AAB status, fasting glucose, HbA1c and age, while the Medium and Large models added predictors of disease progression measured via oral glucose tolerance testing. All models markedly improved granularity regarding personalized risk missing from current categories of stages of T1D. Model derived risk calculations are consistent with the expected reduction of risk with increasing age and increase in risk with higher glucose and lower insulin secretion, illustrating the suitability of the models. Adding glucose and insulin secretion data altered model predicted probabilities within Stages. In those with high 2-hour glucose, a high C-peptide markedly decreased predicted risk; lower C-peptide obviated the age-dependent risk of 2-hour glucose alone, providing a more nuanced estimate of rate of disease progression within Stage 2. While essentially all those with multiple AABs will develop type 1 diabetes, the rate of progression is heterogeneous and not explained by any individual single risk variable. The model-based probabilities developed here provide an adaptable personalized risk calculator to better inform decisions about how and when to monitor disease progression in clinical practice.

A new evaluation system for drug–microbiota interactions

AbstractThe drug response phenotype is determined by a combination of genetic and environmental factors. The high clinical conversion failure rate of gene‐targeted drugs might be attributed to the lack of emphasis on environmental factors and the inherent individual variability in drug response (IVDR). Current evidence suggests that environmental variables, rather than the disease itself, are the primary determinants of both gut microbiota composition and drug metabolism. Additionally, individual differences in gut microbiota create a unique metabolic environment that influences the in vivo processes underlying drug absorption, distribution, metabolism, and excretion (ADME). Here, we discuss how gut microbiota, shaped by both genetic and environmental factors, affects the host's ADME microenvironment within a new evaluation system for drug–microbiota interactions. Furthermore, we propose a new top‐down research approach to investigate the intricate nature of drug–microbiota interactions in vivo. This approach utilizes germ‐free animal models, providing foundation for the development of a new evaluation system for drug–microbiota interactions.

Effect of Fluid Intake on Acute Changes in Plasma Volume: A Randomized Controlled Crossover Pilot Trial.

Plasma volume (PV) undergoes constant and dynamic changes, leading to a large intra-day variability in healthy individuals. Hydration is known to induce PV changes; however, the response to the intake of osmotically different fluids is still not fully understood. In a randomized controlled crossover trial, 18 healthy individuals (10 females) orally received an individual amount of an isotonic sodium-chloride (ISO), Ringer (RIN), or glucose (GLU) solution. Hemoglobin mass (Hbmass) was determined with the optimized carbon monoxide re-breathing method. Fluid-induced changes in PV were subsequently calculated based on capillary hemoglobin concentration ([Hb]) and hematocrit (Hct) before and then every 10 minutes until 120 min (t0-120) after the fluid intake and compared to a control trial arm (CON), where no fluid was administered. Within GLU and CON trial arms, no statistically significant differences from baseline until t120 were found (p > 0.05). In the ISO trial arm, PV was significantly increased at t70 (+138 mL, p = 0.01), t80 (+191 mL, p < 0.01), and t110 (+182 mL, p = 0.01) when compared to t0. Moreover, PV in the ISO trial arm was significantly higher at t70 (p = 0.02), t110 (p = 0.04), and t120 (p = 0.01) when compared to the same time points in the CON trial arm. Within the RIN trial arm, PV was significantly higher between t70 and t90 (+183 mL, p = 0.01) and between t110 (+194 mL, p = 0.03) and t120 (+186 mL, p < 0.01) when compared to t0. These results demonstrated that fluids with a higher content of osmotically active particles lead to acute hemodilution, which is associated with a decrease in [Hb] and Hct. These findings underpin the importance of the hydration state on PV and especially on PV constituent levels in healthy individuals.

Evaluating Attitudes and Preferences towards Walking in Two European Cities

Evaluating Attitudes and Preferences towards Walking in Two European Cities

The spatiotemporal context of individual specialization in resource use and environmental associations.

1. Individual niche specialization is widespread in natural populations and has key implications for higher levels of biological organization. This phenomenon, however, has been primarily quantified in resource niche axes, overlooking individual variation in environmental associations (i.e. abiotic conditions organisms experience). 2. Here, we explore what we can learn from a multidimensional perspective of individual niche specialization that integrates resource use and environmental associations into a common framework. 3. By combining predictions from theory and simple simulations, we illustrate how (i) multidimensional intraspecific niche variation and (ii) the spatiotemporal context of interactions between conspecifics scale up to shape emergent patterns of the population niche. 4. Contemplating individual specialization as a multidimensional, unifying concept across biotic and abiotic niche axes is a fundamental step towards bringing this concept closer to the n-dimensional niche envisioned by Hutchinson.

Major axes of variation in tree demography across global forests

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio‐temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space, totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.

Seasonality in Crotalus durissus venom

Rattlesnakes belonging to the genus Crotalus are widely distributed throughout the Americas. In Brazil, symptoms commonly associated with envenomation by Crotalus durissus collilineatus include myalgia, rhabdomyolysis, renal failure, neurotoxicity, and progressive paralysis, which are related to the protein composition of this venom. Snake venom composition exhibits compositional variability that may reflect geographic distribution, age, captivity, diet, sex, and even individual genetics. Although seasonality is also considered a possible source of variation, there are few reports of such variability in snake venom. In this work, venoms of the same eight C. durissus collilineatus were extracted every three months for two years, to analyze seasonal changes in composition and activities. To this end, venom composition was analyzed by protein quantification, SDS-PAGE, and HPLC, and the LAAO, PLA2 and coagulant activities were measured. Venoms of these C. d. collilineatus showed minor seasonal differences in venom activities and no composition differences were found. LAAO and coagulant activities displayed a pattern of seasonal change, while PLA2 activity seemed to have no seasonality tendency. Also, there are sexual differences, in which males seem to be more stable than females in regard to some activities. Individual variability occurs even in seasonal variation of activities, highlighting the importance of controlling circumstances of venom extraction before comparing results between groups of snakes.

Fractal Analysis of Trabecular Alveolar Bone with Intrabony and Furcation Defects Using Periapical Dental Radiographs

Objective: Fractal analysis (FA) is a non-invasive method that quantitatively measures complex patterned geometric structures present throughout the image. Trabecular morphology of the alveolar bone and the changes occurring in the trabeculae in case of periodontitis can be detected with this method. To examine the periodontal defects in human skull bones using the FA, to compare them with healthy alveolar bone regions. Methods: Furcation and intrabony defects were artificially created in the mandible alveolar bones (n:24). Periapical X-ray images of alveolar bone regions containing teeth with defects were taken using the parallel technique. Fractal analysis was performed by box-counting method using Image J software on images from areas containing healthy and defective trabecular bone. Results: No statistically significant difference was found between the fractal values of healthy tissue and bifurcation defetcs and between the healthy tissue and intrabony defects (p&gt;0.05). Conclusion: Many factors may have affected the outcomes; patient selection, imaging methods, sample size, Region of interest (ROI) selection-location and size, individual and anatomical variations. These variables need to be standardized as much as possible and the limitations of the method need to be improved.

Intervention effects on low performing preschoolers' early mathematical skills: Adding fundamental motor skill practice as a supporting method

BackgroundThis study examined the effects of (1) combined early numeracy and fundamental motor skills (MovEN), (2) early numeracy, and (3) fundamental motor skills intervention programs on children's early mathematical and fundamental motor skills, and how individual background variables affect the effectiveness of these interventions. ProcedureTogether 50 preschoolers participated in the interventions (16 × 45 min sessions). Children's early numeracy, mathematical problem-solving, and fundamental motor skills were measured once before and twice after the interventions. Main findingsThe results showed that the MovEN and early numeracy -interventions were effective in improving children's early numeracy, and mathematical problem-solving. Whereas the MovEN and fundamental motor skills interventions improved children's fundamental motor skills. From individual factors, only updating ability predicted the intervention's effectiveness over and above prior performance. ConclusionThe results suggest that children's early mathematical and fundamental motor skills can be supported effectively at the same time with the MovEN -intervention.

PSV-16 Effect of precision feeding and functional amino acids on immune response and protein metabolism of growing pigs raised in poor sanitary conditions

Abstract The activation of the immune system reduces the nutrient availability for growth and increases the variability among pigs. Functional amino acids (AA) supplementation can reduce the negative effects of immune activation. Additionally, providing daily tailored diets using individual precision feeding (IPF) was shown to account for individual variability. Therefore, we hypothesized that the association of IPF and functional AA supplementation could reduce the negative effect of immune-challenged pigs fed with daily tailored diets. The aim of this study was to assess performance and blood parameters variation of growing pigs under poor sanitary conditions while being fed functional AA 120% above the estimated INRA AA ratios within IPF, compared with a conventional group-phase (GP) feeding system. The sanitary condition was characterized by oral inoculation of 2 × 109 cfu of Salmonella typhimurium and manure spreading on the pen floor on d 0. Sixty gilts (23 ± 2.8 kg body weight; BW) were distributed in a complete randomized block design in a 2 x 2 factorial arrangement composed of 2 diets: CN with 100% INRA AA ratio or AA+ with 120% of the ratio for Met, Thr and Trp; and 2 feeding systems: GP or IPF. GP pigs received a single diet matching the SID Lys requirement of the 80th-percentile pig at the beginning of the trial whereas IPF pigs received a diet tailored daily to each pig requirement. All pigs were group-housed and fed ad libitum for 28 d by automatic feeders. Body weight was measured at d 0 and 28 and feed intake was recorded daily. Blood samples were collected at d 0, 7 and 28. Data were analyzed with diet and feeding systems and their interactions as fixed effects and BW blocks as random effect. Blood parameters were analyzed as repeated measurements over time. The pig was considered the experimental unit. No diet effect or interactions were observed for any variable (P &amp;gt; 0.05), suggesting that only supplementing Met, Trp, and Thr is not enough to support growth during a sanitary challenge (Table 1). Haptoglobin and IgG increased linearly whereas IgA, urea, and creatinine had a quadratic increase over time (P &amp;lt; 0.05; Table 2). The IPF decreased growth performance and increased serum IgA and creatinine (P &amp;lt; 0.05), mostly due to the fact that IPF reduces AA provision compared with GP system. The IPF model, as most mathematical models, does not account for the AA and energy costs related to the immune challenge. Therefore, IPF might have underestimated the requirements of the pigs, and limited the amount of nutrients provided. In conclusion, the combined effect of IPF and functional AA supplementation was not able to reduce the negative effect of the sanitary challenge.

A Bayesian approach for exploring person × environment interaction within the environmental sensitivity meta-framework.

For investigating the individual-environment interplay and individual differences in response to environmental exposures as captured by models of environmental sensitivity including Diathesis-stress, Differential Susceptibility, and Vantage Sensitivity, over the last few years, a series of statistical guidelines have been proposed. However, available solutions suffer of computational problems especially relevant when sample size is not sufficiently large, a common condition in observational and clinical studies. In the current contribution, we propose a Bayesian solution for estimating interaction parameters via Monte Carlo Markov Chains (MCMC), adapting Widaman etal. (Psychological Methods, 17, 2012, 615) Nonlinear Least Squares (NLS) approach. Findings from an applied exemplification and a simulation study showed that with relatively big samples both MCMC and NLS estimates converged on the same results. Conversely, MCMC clearly outperformed NLS, resolving estimation problems and providing more accurate estimates, particularly with small samples and greater residual variance. As the body of research exploring the interplay between individual and environmental variables grows, enabling predictions regarding the form of interaction and the extent of effects, the Bayesian approach could emerge as a feasible and readily applicable solution to numerous computational challenges inherent in existing frequentist methods. This approach holds promise for enhancing the trustworthiness of research outcomes, thereby impacting clinical and applied understanding.

Assessing nasal airway resistance and symmetry: An approach to global perspective through computational fluid dynamics.

This study aimed to explore the variability in nasal airflow patterns among different sexes and populations using computational fluid dynamics (CFD). We focused on evaluating the universality and applicability of dimensionless parameters R (bilateral nasal resistance) and ϕ (nasal flow asymmetry), initially established in a Caucasian Spanish cohort, across a broader spectrum of human populations to assess normal breathing function in healthy airways. In this retrospective study, CT scans from Cambodia (20 males, 20 females), Russia (20 males, 18 females), and Spain (19 males, 19 females) were analyzed. A standardized CFD workflow was implemented to calculate R-ϕ parameters from these scans. Statistical analyses were conducted to assess and compare these parameters across different sexes and populations, emphasizing their distribution and variances. Our results indicated no significant sex-based differences in the R parameter across the populations. However, moderate sexual dimorphism in the ϕ parameter was observed in the Cambodian group. Notably, no geographical differences were found in either R or ϕ parameters, suggesting consistent nasal airflow characteristics across the diverse human groups studied. The study also emphasized the importance of using dimensionless variables to effectively analyze the relationships between form and function in nasal airflow. The observed consistency of R-ϕ parameters across various populations highlights their potential as reliable indicators in both medical practice and further CFD research, particularly in diverse human populations. Our findings suggest the potential applicability of dimensionless CFD parameters in analyzing nasal airflow, highlighting their utility across diverse demographic and geographic contexts. This research advances our understanding of nasal airflow dynamics and underscores the need for additional studies to validate these parameters in broader population cohorts. The approach of employing dimensionless parameters paves the way for future research that eliminates confounding size effects, enabling more accurate comparisons across different populations and sexes. The implications of this study are significant for the advancement of personalized medicine and the development of diagnostic tools that accommodate individual variations in nasal airflow.